activity
20192022
most citedIntegrated Task Assignment and Path Planning for Capacitated Multi-Agent Pickup and Delivery

200 citations · 273 across the 13 of their papers we have counts for

collaborators

16 papers

cs.RO20222 cited

Local Planner Bench: Benchmarking for Local Motion Planning

Max Spahn, Chadi Salmi, Javier Alonso-Mora

Local motion planning is a heavily researched topic in the field of robotics with many promising algorithms being published every year. However, it is difficult and time-consuming…

cs.RO20226 cited

Multi-robot Task Assignment for Aerial Tracking with Viewpoint Constraints

Aaron Ray, Alyssa Pierson, Hai Zhu +2

We address the problem of assigning a team of drones to autonomously capture a set desired shots of a dynamic target in the presence of obstacles. We present a two-stage planning p…

cs.RO2022

Improving Pedestrian Prediction Models with Self-Supervised Continual Learning

Luzia Knoedler, Chadi Salmi, Hai Zhu +2

Autonomous mobile robots require accurate human motion predictions to safely and efficiently navigate among pedestrians, whose behavior may adapt to environmental changes. This pap…

cs.RO20224 cited

Decentralized Probabilistic Multi-Robot Collision Avoidance Using Buffered Uncertainty-Aware Voronoi Cells

Hai Zhu, Bruno Brito, Javier Alonso-Mora

In this paper, we present a decentralized and communication-free collision avoidance approach for multi-robot systems that accounts for both robot localization and sensing uncertai…

cs.MA2021200 cited

Integrated Task Assignment and Path Planning for Capacitated Multi-Agent Pickup and Delivery

Zhe Chen, Javier Alonso-Mora, Xiaoshan Bai +2

Multi-agent Pickup and Delivery (MAPD) is a challenging industrial problem where a team of robots is tasked with transporting a set of tasks, each from an initial location and each…

cs.RO202114 cited

Learning Interaction-aware Guidance Policies for Motion Planning in Dense Traffic Scenarios

Bruno Brito, Achin Agarwal, Javier Alonso-Mora

Autonomous navigation in dense traffic scenarios remains challenging for autonomous vehicles (AVs) because the intentions of other drivers are not directly observable and AVs have…